Simulation 1
Case 1: \(n > p\) - adaptive greedy
simu1_part1_ada <- run_simulation(nb_simu = 500, true_beta = c(1, rep(0,58), 1),
n = 80, n_star = 800, sigma = 1, cor_X = 0.5,
xlim = c(1.035, 1.095), ylim = c(0.02, 0.1),
xlab = expression(PE[y]),
ylab = expression(MSE[beta]),
title = "Simulation 1: n > p",
adaptive = TRUE)

kable(simu1_part1_ada)
| LS |
3.924397 |
0.0520607 |
4.7643774 |
0.0788026 |
0.0 |
100.0 |
2.000 |
58.000 |
60.000 |
| AIC |
1.581485 |
0.0258145 |
0.7567005 |
0.0502997 |
5.4 |
99.0 |
1.990 |
10.520 |
12.510 |
| BIC |
1.080430 |
0.0060340 |
0.0782325 |
0.0091298 |
49.4 |
98.8 |
1.988 |
1.164 |
3.152 |
| HQ |
1.216138 |
0.0196712 |
0.2371755 |
0.0217632 |
21.2 |
98.8 |
1.988 |
3.976 |
5.964 |
| lasso |
1.129553 |
0.0054523 |
0.1352864 |
0.0038669 |
3.4 |
100.0 |
2.000 |
8.324 |
10.324 |
| PDC |
1.057575 |
0.0034222 |
0.0429433 |
0.0053703 |
59.8 |
98.0 |
1.978 |
0.520 |
2.498 |
| enet |
1.166245 |
0.0074518 |
0.1749347 |
0.0061593 |
2.0 |
100.0 |
2.000 |
11.168 |
13.168 |
| alasso |
1.045711 |
0.0037980 |
0.0354535 |
0.0025080 |
67.8 |
100.0 |
2.000 |
0.936 |
2.936 |
| MCP |
1.072988 |
0.0051792 |
0.0298685 |
0.0021546 |
56.4 |
100.0 |
2.000 |
1.350 |
3.350 |
| SCAD |
1.078244 |
0.0041694 |
0.0327290 |
0.0022017 |
25.0 |
100.0 |
2.000 |
2.904 |
4.904 |
Case 2: \(n > p\) - non-adaptive greedy
simu1_part1_non_ada <- run_simulation(nb_simu = 500, true_beta = c(1, rep(0,58), 1),
n = 80, n_star = 800, sigma = 1, cor_X = 0.5,
xlim = c(1.035, 1.095), ylim = c(0.02, 0.1),
xlab = expression(PE[y]),
ylab = expression(MSE[beta]),
title = "Simulation 1: n > p",
adaptive = FALSE)

kable(simu1_part1_non_ada)
| LS |
3.924397 |
0.0520607 |
4.7643774 |
0.0788026 |
0.0 |
100 |
2 |
58.000 |
60.000 |
| AIC |
1.514825 |
0.0232021 |
0.6381180 |
0.0309768 |
1.0 |
100 |
2 |
9.250 |
11.250 |
| BIC |
1.134133 |
0.0093528 |
0.1333654 |
0.0083030 |
27.0 |
100 |
2 |
1.742 |
3.742 |
| HQ |
1.292105 |
0.0114149 |
0.3335967 |
0.0174288 |
7.8 |
100 |
2 |
4.584 |
6.584 |
| lasso |
1.129553 |
0.0054523 |
0.1352864 |
0.0038669 |
3.4 |
100 |
2 |
8.324 |
10.324 |
| PDC |
1.066817 |
0.0045007 |
0.0557219 |
0.0073714 |
56.2 |
100 |
2 |
0.588 |
2.588 |
| enet |
1.166245 |
0.0074518 |
0.1749347 |
0.0061593 |
2.0 |
100 |
2 |
11.168 |
13.168 |
| alasso |
1.045711 |
0.0037980 |
0.0354535 |
0.0025080 |
67.8 |
100 |
2 |
0.936 |
2.936 |
| MCP |
1.072988 |
0.0051792 |
0.0298685 |
0.0021546 |
56.4 |
100 |
2 |
1.350 |
3.350 |
| SCAD |
1.078244 |
0.0041694 |
0.0327290 |
0.0022017 |
25.0 |
100 |
2 |
2.904 |
4.904 |
Case 3: \(n < p\) - adaptive greedy
simu1_part2_ada <- run_simulation(nb_simu = 500, true_beta = c(1, rep(0, 58), 1, rep(0, 100)),
n = 80, n_star = 800, sigma = 1, cor_X = 0.5,
xlim = c(1.045,1.22), ylim = c(0.03,0.23),
xlab = expression(PE[y]),
ylab = expression(MSE[beta]),
title = "Simulation 1: n < p",
adaptive = TRUE)

kable(simu1_part2_ada)
| LS |
1.785228 |
0.0123505 |
0.9016844 |
0.0170075 |
0.0 |
100 |
2 |
31.000 |
33.000 |
| AIC |
1.452693 |
0.0131253 |
0.4715656 |
0.0142591 |
1.0 |
100 |
2 |
6.342 |
8.342 |
| BIC |
1.198411 |
0.0085915 |
0.1957703 |
0.0106081 |
22.2 |
100 |
2 |
2.104 |
4.104 |
| HQ |
1.323303 |
0.0130418 |
0.3553142 |
0.0136168 |
4.4 |
100 |
2 |
4.172 |
6.172 |
| lasso |
1.175958 |
0.0078497 |
0.1829157 |
0.0052767 |
1.6 |
100 |
2 |
11.778 |
13.778 |
| PDC |
1.090815 |
0.0062457 |
0.0916089 |
0.0065994 |
47.6 |
100 |
2 |
0.798 |
2.798 |
| enet |
1.218933 |
0.0072229 |
0.2385542 |
0.0097881 |
0.6 |
100 |
2 |
16.204 |
18.204 |
| alasso |
1.056450 |
0.0043868 |
0.0409949 |
0.0030151 |
63.6 |
100 |
2 |
1.106 |
3.106 |
| MCP |
1.081824 |
0.0034671 |
0.0394910 |
0.0035240 |
46.6 |
100 |
2 |
1.970 |
3.970 |
| SCAD |
1.090216 |
0.0045551 |
0.0492014 |
0.0029099 |
12.4 |
100 |
2 |
5.564 |
7.564 |
Case 4: \(n < p\) - non-adaptive greedy
simu1_part2_non_ada <- run_simulation(nb_simu = 500, true_beta = c(1, rep(0, 58), 1, rep(0, 100)),
n = 80, n_star = 800, sigma = 1, cor_X = 0.5,
xlim = c(1.045,1.22), ylim = c(0.03,0.23),
xlab = expression(PE[y]),
ylab = expression(MSE[beta]),
title = "Simulation 1: n < p",
adaptive = FALSE)

kable(simu1_part2_non_ada)
| LS |
1.785228 |
0.0123505 |
0.9016844 |
0.0170075 |
0.0 |
100 |
2 |
31.000 |
33.000 |
| AIC |
1.385566 |
0.0122123 |
0.4218037 |
0.0112756 |
0.0 |
100 |
2 |
6.050 |
8.050 |
| BIC |
1.198981 |
0.0065862 |
0.1960937 |
0.0092454 |
14.8 |
100 |
2 |
2.128 |
4.128 |
| HQ |
1.299758 |
0.0092714 |
0.3113019 |
0.0125721 |
2.8 |
100 |
2 |
4.030 |
6.030 |
| lasso |
1.175958 |
0.0078497 |
0.1829157 |
0.0052767 |
1.6 |
100 |
2 |
11.778 |
13.778 |
| PDC |
1.098539 |
0.0062526 |
0.1015345 |
0.0057471 |
42.0 |
100 |
2 |
0.890 |
2.890 |
| enet |
1.218933 |
0.0072229 |
0.2385542 |
0.0097881 |
0.6 |
100 |
2 |
16.204 |
18.204 |
| alasso |
1.056450 |
0.0043868 |
0.0409949 |
0.0030151 |
63.6 |
100 |
2 |
1.106 |
3.106 |
| MCP |
1.081824 |
0.0034671 |
0.0394910 |
0.0035240 |
46.6 |
100 |
2 |
1.970 |
3.970 |
| SCAD |
1.090216 |
0.0045551 |
0.0492014 |
0.0029099 |
12.4 |
100 |
2 |
5.564 |
7.564 |
Simulation 2
Case 1: \(n > p\) - adaptive greedy
simu2_part1_ada <- run_simulation(nb_simu = 500, true_beta = rep(c(0.3, 0), 5),
n = 100, n_star = 1000, sigma = 1, cor_X = 0.75,
xlim = c(1.065,1.17), ylim = c(0.18,0.46),
xlab = expression(PE[y]),
ylab = expression(MSE[beta]),
title = "Simulation 2: n > p",
adaptive = TRUE)

kable(simu2_part1_ada)
| LS |
1.107841 |
0.0035288 |
0.3329839 |
0.0121383 |
0.0 |
100.0 |
5.000 |
5.000 |
10.000 |
| AIC |
1.124838 |
0.0038600 |
0.3514957 |
0.0147284 |
3.8 |
7.8 |
3.134 |
0.856 |
3.990 |
| BIC |
1.155585 |
0.0044200 |
0.4046674 |
0.0210016 |
0.4 |
0.6 |
2.586 |
0.532 |
3.118 |
| HQ |
1.136904 |
0.0042594 |
0.3599505 |
0.0132298 |
1.4 |
1.8 |
2.868 |
0.658 |
3.526 |
| lasso |
1.078078 |
0.0037695 |
0.2066077 |
0.0078130 |
2.6 |
63.0 |
4.556 |
2.680 |
7.236 |
| PDC |
1.144741 |
0.0047182 |
0.3735564 |
0.0156125 |
0.4 |
0.6 |
2.692 |
0.568 |
3.260 |
| enet |
1.075393 |
0.0030004 |
0.1956800 |
0.0080185 |
0.8 |
71.8 |
4.680 |
3.054 |
7.734 |
| alasso |
1.091444 |
0.0040757 |
0.2487335 |
0.0112976 |
5.8 |
37.0 |
4.038 |
1.794 |
5.832 |
| MCP |
1.138029 |
0.0032298 |
0.3635244 |
0.0172100 |
5.2 |
34.8 |
3.772 |
2.018 |
5.790 |
| SCAD |
1.136440 |
0.0039713 |
0.3589930 |
0.0131578 |
5.8 |
37.4 |
3.902 |
2.174 |
6.076 |
Case 2: \(n > p\) - non-adaptive greedy
simu2_part1_nonada <- run_simulation(nb_simu = 500, true_beta = rep(c(0.3, 0), 5),
n = 100, n_star = 1000, sigma = 1, cor_X = 0.75,
xlim = c(1.065,1.17), ylim = c(0.18,0.46),
xlab = expression(PE[y]),
ylab = expression(MSE[beta]),
title = "Simulation 2: n > p",
adaptive = FALSE)

kable(simu2_part1_nonada)
| LS |
1.107841 |
0.0035288 |
0.3329839 |
0.0121383 |
0.0 |
100.0 |
5.000 |
5.000 |
10.000 |
| AIC |
1.125236 |
0.0036476 |
0.3624555 |
0.0115668 |
2.2 |
6.4 |
3.006 |
1.082 |
4.088 |
| BIC |
1.159894 |
0.0035174 |
0.4539168 |
0.0173506 |
0.4 |
0.6 |
2.374 |
0.758 |
3.132 |
| HQ |
1.135682 |
0.0043017 |
0.3898845 |
0.0158302 |
2.0 |
2.8 |
2.708 |
0.870 |
3.578 |
| lasso |
1.078078 |
0.0037695 |
0.2066077 |
0.0078130 |
2.6 |
63.0 |
4.556 |
2.680 |
7.236 |
| PDC |
1.144557 |
0.0041778 |
0.4204443 |
0.0186504 |
1.4 |
1.6 |
2.502 |
0.824 |
3.326 |
| enet |
1.075393 |
0.0030004 |
0.1956800 |
0.0080185 |
0.8 |
71.8 |
4.680 |
3.054 |
7.734 |
| alasso |
1.091444 |
0.0040757 |
0.2487335 |
0.0112976 |
5.8 |
37.0 |
4.038 |
1.794 |
5.832 |
| MCP |
1.138029 |
0.0032298 |
0.3635244 |
0.0172100 |
5.2 |
34.8 |
3.772 |
2.018 |
5.790 |
| SCAD |
1.136440 |
0.0039713 |
0.3589930 |
0.0131578 |
5.8 |
37.4 |
3.902 |
2.174 |
6.076 |
Case 3: \(n < p\) - adaptive
simu2_part2_ada <- run_simulation(nb_simu = 500,
true_beta = c(rep(c(0.3, 0), 5), rep(0, 100)),
n = 100, n_star = 1000, sigma = 1, cor_X = 0.75,
xlim = c(1.14,1.37), ylim = c(0.21,0.74),
xlab = expression(PE[y]),
ylab = expression(MSE[beta]),
title = "Simulation 2: n < p",
adaptive = TRUE)

kable(simu2_part2_ada)
| LS |
1.650416 |
0.0101951 |
1.5687304 |
0.0341128 |
0.0 |
99.8 |
4.998 |
34.002 |
39.000 |
| AIC |
1.403845 |
0.0100389 |
0.7874925 |
0.0253773 |
0.0 |
3.8 |
2.838 |
6.016 |
8.854 |
| BIC |
1.291410 |
0.0060477 |
0.6117670 |
0.0113472 |
0.0 |
0.2 |
2.316 |
2.230 |
4.546 |
| HQ |
1.340386 |
0.0084212 |
0.6765585 |
0.0174947 |
0.0 |
1.6 |
2.626 |
4.040 |
6.666 |
| lasso |
1.165019 |
0.0055075 |
0.2577517 |
0.0078091 |
0.6 |
43.4 |
4.240 |
9.760 |
14.000 |
| PDC |
1.271483 |
0.0053393 |
0.5808807 |
0.0150697 |
0.0 |
0.0 |
1.974 |
1.098 |
3.072 |
| enet |
1.160756 |
0.0045681 |
0.2413781 |
0.0049370 |
0.2 |
60.2 |
4.514 |
13.892 |
18.406 |
| alasso |
1.183282 |
0.0060611 |
0.3603656 |
0.0137988 |
1.0 |
10.4 |
3.064 |
2.436 |
5.500 |
| MCP |
1.283560 |
0.0057373 |
0.5832792 |
0.0159249 |
0.2 |
0.8 |
2.174 |
3.558 |
5.732 |
| SCAD |
1.269043 |
0.0063063 |
0.4602072 |
0.0091509 |
0.8 |
10.0 |
3.040 |
5.790 |
8.830 |
Case 4: \(n < p\) - non-adaptive
simu2_part2_non_ada <- run_simulation(nb_simu = 500,
true_beta = c(rep(c(0.3, 0), 5), rep(0, 100)),
n = 100, n_star = 1000, sigma = 1, cor_X = 0.75,
xlim = c(1.14,1.37), ylim = c(0.21,0.74),
xlab = expression(PE[y]),
ylab = expression(MSE[beta]),
title = "Simulation 2: n < p",
adaptive = FALSE)

kable(simu2_part2_non_ada)
| LS |
1.650416 |
0.0101951 |
1.5687304 |
0.0341128 |
0.0 |
99.8 |
4.998 |
34.002 |
39.000 |
| AIC |
1.356395 |
0.0088333 |
0.6652823 |
0.0183908 |
0.0 |
3.6 |
2.746 |
5.622 |
8.368 |
| BIC |
1.278110 |
0.0077329 |
0.6015461 |
0.0102443 |
0.2 |
0.4 |
2.180 |
2.184 |
4.364 |
| HQ |
1.319665 |
0.0089797 |
0.6172520 |
0.0133371 |
0.2 |
2.0 |
2.488 |
3.792 |
6.280 |
| lasso |
1.165019 |
0.0055075 |
0.2577517 |
0.0078091 |
0.6 |
43.4 |
4.240 |
9.760 |
14.000 |
| PDC |
1.265392 |
0.0077299 |
0.5991625 |
0.0114898 |
0.2 |
0.2 |
1.864 |
1.192 |
3.056 |
| enet |
1.160756 |
0.0045681 |
0.2413781 |
0.0049370 |
0.2 |
60.2 |
4.514 |
13.892 |
18.406 |
| alasso |
1.183282 |
0.0060611 |
0.3603656 |
0.0137988 |
1.0 |
10.4 |
3.064 |
2.436 |
5.500 |
| MCP |
1.283560 |
0.0057373 |
0.5832792 |
0.0159249 |
0.2 |
0.8 |
2.174 |
3.558 |
5.732 |
| SCAD |
1.269043 |
0.0063063 |
0.4602072 |
0.0091509 |
0.8 |
10.0 |
3.040 |
5.790 |
8.830 |
Simulation 3
Case 1: \(n > p\) - adaptive greedy
beta <- c(rep(c(2,0,1),2),rep(0,16),rep(0.1,6),rep(0,16),rep(c(2,0,1),2))
simu3_part1_ada <- run_simulation(nb_simu = 500, true_beta = beta,
n = 100, n_star = 1000, sigma = 2, cor_X = 0.5,
xlim = c(4.73,5.4), ylim = c(0.79,1.8),
xlab = expression(PE[y]),
ylab = expression(MSE[beta]),
title = "Simulation 3: n > p",
adaptive = TRUE)

kable(simu3_part1_ada)
| LS |
7.828768 |
0.0539561 |
6.3269382 |
0.1089886 |
0 |
100.0 |
14.000 |
36.000 |
50.000 |
| AIC |
5.602199 |
0.0407343 |
2.3001445 |
0.1069784 |
0 |
0.0 |
8.946 |
4.972 |
13.918 |
| BIC |
4.984983 |
0.0364475 |
1.1753320 |
0.0678564 |
0 |
0.0 |
8.086 |
1.230 |
9.316 |
| HQ |
5.217643 |
0.0629048 |
1.5831001 |
0.0692687 |
0 |
0.0 |
8.502 |
2.742 |
11.244 |
| lasso |
5.067051 |
0.0277870 |
1.2319757 |
0.0320709 |
0 |
0.2 |
10.146 |
9.974 |
20.120 |
| PDC |
5.048466 |
0.0509589 |
1.3548679 |
0.0735508 |
0 |
0.0 |
7.392 |
0.360 |
7.752 |
| enet |
5.126117 |
0.0249846 |
1.3744623 |
0.0363623 |
0 |
1.8 |
10.474 |
12.024 |
22.498 |
| alasso |
4.803297 |
0.0314939 |
0.9325193 |
0.0448793 |
0 |
0.0 |
8.678 |
2.524 |
11.202 |
| MCP |
5.233635 |
0.0527333 |
1.0135877 |
0.0516727 |
0 |
0.0 |
8.730 |
2.936 |
11.666 |
| SCAD |
5.201045 |
0.0463538 |
1.0172687 |
0.0584409 |
0 |
0.0 |
9.450 |
5.480 |
14.930 |
Case 2: \(n > p\) - non-adaptive greedy
beta <- c(rep(c(2,0,1),2),rep(0,16),rep(0.1,6),rep(0,16),rep(c(2,0,1),2))
simu3_part1_nonada <- run_simulation(nb_simu = 500, true_beta = beta,
n = 100, n_star = 1000, sigma = 2, cor_X = 0.5,
xlim = c(4.73,5.4), ylim = c(0.79,1.8),
xlab = expression(PE[y]),
ylab = expression(MSE[beta]),
title = "Simulation 3: n > p",
adaptive = FALSE)

kable(simu3_part1_nonada)
| LS |
7.828768 |
0.0539561 |
6.3269382 |
0.1089886 |
0 |
100.0 |
14.000 |
36.000 |
50.000 |
| AIC |
5.471716 |
0.0418450 |
1.8685351 |
0.0647247 |
0 |
0.0 |
9.028 |
4.572 |
13.600 |
| BIC |
4.913370 |
0.0289821 |
1.0343625 |
0.0446144 |
0 |
0.0 |
8.198 |
1.196 |
9.394 |
| HQ |
5.133586 |
0.0497034 |
1.4275142 |
0.0659176 |
0 |
0.0 |
8.612 |
2.578 |
11.190 |
| lasso |
5.067051 |
0.0277870 |
1.2319757 |
0.0320709 |
0 |
0.2 |
10.146 |
9.974 |
20.120 |
| PDC |
4.996859 |
0.0439417 |
1.2350775 |
0.0902718 |
0 |
0.0 |
7.558 |
0.526 |
8.084 |
| enet |
5.126117 |
0.0249846 |
1.3744623 |
0.0363623 |
0 |
1.8 |
10.474 |
12.024 |
22.498 |
| alasso |
4.803297 |
0.0314939 |
0.9325193 |
0.0448793 |
0 |
0.0 |
8.678 |
2.524 |
11.202 |
| MCP |
5.233635 |
0.0527333 |
1.0135877 |
0.0516727 |
0 |
0.0 |
8.730 |
2.936 |
11.666 |
| SCAD |
5.201045 |
0.0463538 |
1.0172687 |
0.0584409 |
0 |
0.0 |
9.450 |
5.480 |
14.930 |
Case 3: \(n < p\) - adaptive
beta <- c(rep(c(2,0,1),2),rep(0,16),rep(0.1,6),rep(0,16),rep(c(2,0,1),2),
rep(0,100))
simu3_part2_ada <- run_simulation(nb_simu = 500, true_beta = beta,
n = 100, n_star = 1000, sigma = 2, cor_X = 0.5,
xlim = c(4.85,5.9), ylim = c(1,2),
xlab = expression(PE[y]),
ylab = expression(MSE[beta]),
title = "Simulation 3: n < p",
adaptive = TRUE)

kable(simu3_part2_ada)
| LS |
6.981891 |
0.0610234 |
3.765791 |
0.0692500 |
0 |
0.4 |
9.138 |
29.862 |
39.000 |
| AIC |
5.638632 |
0.0468071 |
1.915825 |
0.0537250 |
0 |
0.0 |
8.098 |
4.624 |
12.722 |
| BIC |
5.058629 |
0.0493449 |
1.212897 |
0.0534257 |
0 |
0.0 |
7.786 |
1.370 |
9.156 |
| HQ |
5.326638 |
0.0583424 |
1.570145 |
0.0536998 |
0 |
0.0 |
7.954 |
2.734 |
10.688 |
| lasso |
5.635840 |
0.0346758 |
1.665008 |
0.0314404 |
0 |
0.0 |
9.334 |
18.934 |
28.268 |
| PDC |
5.061261 |
0.0674485 |
1.361253 |
0.1021703 |
0 |
0.0 |
7.264 |
0.564 |
7.828 |
| enet |
5.792712 |
0.0358061 |
1.841099 |
0.0443238 |
0 |
0.2 |
9.516 |
23.152 |
32.668 |
| alasso |
4.994438 |
0.0309109 |
1.134744 |
0.0420539 |
0 |
0.0 |
8.194 |
3.126 |
11.320 |
| MCP |
5.637378 |
0.0572940 |
1.459303 |
0.0736045 |
0 |
0.0 |
8.114 |
4.784 |
12.898 |
| SCAD |
5.592650 |
0.0564631 |
1.518394 |
0.0695838 |
0 |
0.0 |
8.888 |
11.420 |
20.308 |
Case 4: \(n < p\) - non-adaptive
beta <- c(rep(c(2,0,1),2),rep(0,16),rep(0.1,6),rep(0,16),rep(c(2,0,1),2),
rep(0,100))
simu3_part2_non_ada <- run_simulation(nb_simu = 500, true_beta = beta,
n = 100, n_star = 1000, sigma = 2, cor_X = 0.5,
xlim = c(4.85,5.9), ylim = c(1,2),
xlab = expression(PE[y]),
ylab = expression(MSE[beta]),
title = "Simulation 3: n < p",
adaptive = FALSE)

kable(simu3_part2_non_ada)
| LS |
6.981891 |
0.0610234 |
3.765791 |
0.0692500 |
0 |
0.4 |
9.138 |
29.862 |
39.000 |
| AIC |
5.562745 |
0.0408023 |
1.821001 |
0.0558496 |
0 |
0.0 |
8.140 |
4.546 |
12.686 |
| BIC |
5.107543 |
0.0450648 |
1.264909 |
0.0722063 |
0 |
0.0 |
7.760 |
1.532 |
9.292 |
| HQ |
5.348961 |
0.0416001 |
1.540760 |
0.0444740 |
0 |
0.0 |
7.980 |
2.838 |
10.818 |
| lasso |
5.635840 |
0.0346758 |
1.665008 |
0.0314404 |
0 |
0.0 |
9.334 |
18.934 |
28.268 |
| PDC |
5.136446 |
0.0495950 |
1.457847 |
0.1109942 |
0 |
0.0 |
7.258 |
0.668 |
7.926 |
| enet |
5.792712 |
0.0358061 |
1.841099 |
0.0443238 |
0 |
0.2 |
9.516 |
23.152 |
32.668 |
| alasso |
4.994438 |
0.0309109 |
1.134744 |
0.0420539 |
0 |
0.0 |
8.194 |
3.126 |
11.320 |
| MCP |
5.637378 |
0.0572940 |
1.459303 |
0.0736045 |
0 |
0.0 |
8.114 |
4.784 |
12.898 |
| SCAD |
5.592650 |
0.0564631 |
1.518394 |
0.0695838 |
0 |
0.0 |
8.888 |
11.420 |
20.308 |
Simulation 4
Case 1: \(n > p\) - adaptive greedy
beta <- c(rep(c(2,0,1),2),rep(0,16),rep(0.1,6),rep(0,16),rep(c(2,0,1),2))
simu4_part1_ada <- run_simulation(nb_simu = 500, true_beta = beta,
n = 100, n_star = 1000, sigma = 2, cor_X = 0.5,
xlim = c(0.73,100.4), ylim = c(0.0079,20.8),
xlab = expression(PE[y]),
ylab = expression(MSE[beta]),
title = "Simulation 4: n > p",
adaptive = TRUE, omitted_variables = 1)

kable(simu4_part1_ada)
| LS |
13.502791 |
0.1501429 |
10.707603 |
0.1837823 |
0 |
0 |
49.000 |
0 |
49.000 |
| AIC |
10.171847 |
0.0852397 |
4.680953 |
0.1966095 |
0 |
0 |
13.262 |
0 |
13.262 |
| BIC |
9.288934 |
0.0568300 |
3.237664 |
0.1084220 |
0 |
0 |
8.066 |
0 |
8.066 |
| HQ |
9.509905 |
0.0842522 |
3.468800 |
0.1150142 |
0 |
0 |
10.158 |
0 |
10.158 |
| lasso |
8.678201 |
0.0460419 |
2.015333 |
0.0621440 |
0 |
0 |
19.092 |
0 |
19.092 |
| PDC |
9.696391 |
0.0804393 |
3.886826 |
0.1249451 |
0 |
0 |
6.090 |
0 |
6.090 |
| enet |
8.814902 |
0.0393679 |
2.197442 |
0.0566599 |
0 |
0 |
21.730 |
0 |
21.730 |
| alasso |
8.614828 |
0.0564466 |
2.151635 |
0.0899776 |
0 |
0 |
10.972 |
0 |
10.972 |
| MCP |
9.477908 |
0.0819999 |
3.036092 |
0.0992974 |
0 |
0 |
11.008 |
0 |
11.008 |
| SCAD |
9.378062 |
0.0614218 |
2.977569 |
0.0896044 |
0 |
0 |
14.468 |
0 |
14.468 |
Case 2: \(n > p\) - nonadaptive greedy
beta <- c(rep(c(2,0,1),2),rep(0,16),rep(0.1,6),rep(0,16),rep(c(2,0,1),2))
simu4_part1_nonada <- run_simulation(nb_simu = 500, true_beta = beta,
n = 100, n_star = 1000, sigma = 2, cor_X = 0.5,
xlim = c(0.73,100.4), ylim = c(0.0079,20.8),
xlab = expression(PE[y]),
ylab = expression(MSE[beta]),
title = "Simulation 4: n > p",
adaptive = FALSE, omitted_variables = 1)

kable(simu4_part1_nonada)
| LS |
13.502791 |
0.1501429 |
10.707603 |
0.1837823 |
0 |
0 |
49.000 |
0 |
49.000 |
| AIC |
9.793129 |
0.0768132 |
3.784237 |
0.1184813 |
0 |
0 |
12.892 |
0 |
12.892 |
| BIC |
9.241664 |
0.0697646 |
3.055688 |
0.0801707 |
0 |
0 |
8.176 |
0 |
8.176 |
| HQ |
9.456914 |
0.0992046 |
3.329390 |
0.0972033 |
0 |
0 |
10.380 |
0 |
10.380 |
| lasso |
8.678201 |
0.0460419 |
2.015333 |
0.0621440 |
0 |
0 |
19.092 |
0 |
19.092 |
| PDC |
9.651446 |
0.0670652 |
3.882546 |
0.0998996 |
0 |
0 |
6.306 |
0 |
6.306 |
| enet |
8.814902 |
0.0393679 |
2.197442 |
0.0566599 |
0 |
0 |
21.730 |
0 |
21.730 |
| alasso |
8.614828 |
0.0564466 |
2.151635 |
0.0899776 |
0 |
0 |
10.972 |
0 |
10.972 |
| MCP |
9.477908 |
0.0819999 |
3.036092 |
0.0992974 |
0 |
0 |
11.008 |
0 |
11.008 |
| SCAD |
9.378062 |
0.0614218 |
2.977569 |
0.0896044 |
0 |
0 |
14.468 |
0 |
14.468 |
Case 3: \(n < p\) - adaptive greedy
beta <- c(rep(c(2,0,1),2),rep(0,16),rep(0.1,6),rep(0,16),rep(c(2,0,1),2), rep(0, 100))
simu4_part2_ada <- run_simulation(nb_simu = 500, true_beta = beta,
n = 100, n_star = 1000, sigma = 2, cor_X = 0.5,
xlim = c(0.73,100.4), ylim = c(0.0079,20.8),
xlab = expression(PE[y]),
ylab = expression(MSE[beta]),
title = "Simulation 4: n < p",
adaptive = TRUE, omitted_variables = 1)

kable(simu4_part2_ada)
| LS |
11.993168 |
0.0918683 |
6.166943 |
0.0984212 |
0 |
0 |
39.000 |
0 |
39.000 |
| AIC |
10.267386 |
0.0995894 |
3.877167 |
0.1223970 |
0 |
0 |
12.792 |
0 |
12.792 |
| BIC |
9.653047 |
0.0716499 |
3.379400 |
0.0926498 |
0 |
0 |
8.548 |
0 |
8.548 |
| HQ |
9.807477 |
0.0833390 |
3.467016 |
0.0991983 |
0 |
0 |
10.586 |
0 |
10.586 |
| lasso |
9.581549 |
0.0545424 |
2.682683 |
0.0620017 |
0 |
0 |
26.404 |
0 |
26.404 |
| PDC |
9.871702 |
0.0776319 |
3.934555 |
0.0797900 |
0 |
0 |
6.214 |
0 |
6.214 |
| enet |
9.754135 |
0.0581014 |
2.806577 |
0.0570407 |
0 |
0 |
31.418 |
0 |
31.418 |
| alasso |
9.075474 |
0.0560001 |
2.579230 |
0.0734337 |
0 |
0 |
10.940 |
0 |
10.940 |
| MCP |
10.184737 |
0.0721937 |
4.065031 |
0.1145714 |
0 |
0 |
11.216 |
0 |
11.216 |
| SCAD |
10.142393 |
0.0667124 |
3.857304 |
0.0715728 |
0 |
0 |
18.320 |
0 |
18.320 |
Case 4: \(n < p\) - nonadaptive greedy
beta <- c(rep(c(2,0,1),2),rep(0,16),rep(0.1,6),rep(0,16),rep(c(2,0,1),2), rep(0, 100))
simu4_part2_nonada <- run_simulation(nb_simu = 500, true_beta = beta,
n = 100, n_star = 1000, sigma = 2, cor_X = 0.5,
xlim = c(0.73,100.4), ylim = c(0.0079,20.8),
xlab = expression(PE[y]),
ylab = expression(MSE[beta]),
title = "Simulation 4: n < p",
adaptive = FALSE, omitted_variables = 1)

kable(simu4_part2_nonada)
| LS |
11.993168 |
0.0918683 |
6.166943 |
0.0984212 |
0 |
0 |
39.000 |
0 |
39.000 |
| AIC |
10.147548 |
0.0615976 |
3.783625 |
0.0653097 |
0 |
0 |
12.626 |
0 |
12.626 |
| BIC |
9.672819 |
0.0627906 |
3.512746 |
0.1176478 |
0 |
0 |
8.550 |
0 |
8.550 |
| HQ |
9.829220 |
0.0576269 |
3.497726 |
0.1063502 |
0 |
0 |
10.550 |
0 |
10.550 |
| lasso |
9.581549 |
0.0545424 |
2.682683 |
0.0620017 |
0 |
0 |
26.404 |
0 |
26.404 |
| PDC |
9.951037 |
0.0692510 |
4.057780 |
0.1249516 |
0 |
0 |
6.380 |
0 |
6.380 |
| enet |
9.754135 |
0.0581014 |
2.806577 |
0.0570407 |
0 |
0 |
31.418 |
0 |
31.418 |
| alasso |
9.075474 |
0.0560001 |
2.579230 |
0.0734337 |
0 |
0 |
10.940 |
0 |
10.940 |
| MCP |
10.184737 |
0.0721937 |
4.065031 |
0.1145714 |
0 |
0 |
11.216 |
0 |
11.216 |
| SCAD |
10.142393 |
0.0667124 |
3.857304 |
0.0715728 |
0 |
0 |
18.320 |
0 |
18.320 |
Simulation 5
Case 1: \(n > p\) - adaptive greedy
beta <- c(3,rep(0,5),1,rep(0,10),rep(0.05,3),rep(0,10),2,rep(0,20))
simu5_part1_ada <- run_simulation(nb_simu = 500, true_beta = beta,
n = 100, n_star = 1000, sigma = 3, cor_X = 0.25,
xlim = c(19.3,20.2), ylim = c(1.6,2.75),
xlab = expression(PE[y]),
ylab = expression(MSE[beta]),
title = "Simulation 5: n > p",
adaptive = TRUE, omitted_variables = 1)

kable(simu5_part1_ada)
| LS |
35.21969 |
0.3187061 |
19.611517 |
0.3362240 |
0 |
0 |
50.000 |
0 |
50.000 |
| AIC |
23.81532 |
0.2259463 |
6.564957 |
0.2060844 |
0 |
0 |
8.434 |
0 |
8.434 |
| BIC |
19.94307 |
0.0804733 |
2.505281 |
0.1080523 |
0 |
0 |
2.748 |
0 |
2.748 |
| HQ |
21.53516 |
0.1586480 |
4.101247 |
0.1566812 |
0 |
0 |
4.952 |
0 |
4.952 |
| lasso |
19.67917 |
0.0716364 |
2.307344 |
0.0708563 |
0 |
0 |
8.512 |
0 |
8.512 |
| PDC |
19.57266 |
0.0811335 |
1.807336 |
0.0602241 |
0 |
0 |
1.878 |
0 |
1.878 |
| enet |
19.85348 |
0.0655296 |
2.461787 |
0.0721343 |
0 |
0 |
11.622 |
0 |
11.622 |
| alasso |
19.63743 |
0.0829160 |
2.005477 |
0.0491488 |
0 |
0 |
2.940 |
0 |
2.940 |
| MCP |
19.82289 |
0.0748150 |
1.979799 |
0.0488847 |
0 |
0 |
4.310 |
0 |
4.310 |
| SCAD |
19.80302 |
0.1020472 |
2.085949 |
0.0606429 |
0 |
0 |
6.824 |
0 |
6.824 |
Case 2: \(n > p\) - nonadaptive greedy
beta <- c(3,rep(0,5),1,rep(0,10),rep(0.05,3),rep(0,10),2,rep(0,20))
simu5_part1_nonada <- run_simulation(nb_simu = 500, true_beta = beta,
n = 100, n_star = 1000, sigma = 3, cor_X = 0.25,
xlim = c(19.3,20.2), ylim = c(1.6,2.75),
xlab = expression(PE[y]),
ylab = expression(MSE[beta]),
title = "Simulation 5: n > p",
adaptive = FALSE, omitted_variables = 1)

kable(simu5_part1_nonada)
| LS |
35.21969 |
0.3187061 |
19.611517 |
0.3362240 |
0 |
0 |
50.000 |
0 |
50.000 |
| AIC |
23.20874 |
0.2026071 |
5.898750 |
0.2338397 |
0 |
0 |
8.110 |
0 |
8.110 |
| BIC |
19.95860 |
0.0791702 |
2.551035 |
0.0919496 |
0 |
0 |
2.908 |
0 |
2.908 |
| HQ |
21.28517 |
0.1197085 |
4.073351 |
0.1319092 |
0 |
0 |
4.990 |
0 |
4.990 |
| lasso |
19.67917 |
0.0716364 |
2.307344 |
0.0708563 |
0 |
0 |
8.512 |
0 |
8.512 |
| PDC |
19.56326 |
0.0909917 |
1.778441 |
0.0453945 |
0 |
0 |
1.916 |
0 |
1.916 |
| enet |
19.85348 |
0.0655296 |
2.461787 |
0.0721343 |
0 |
0 |
11.622 |
0 |
11.622 |
| alasso |
19.63743 |
0.0829160 |
2.005477 |
0.0491488 |
0 |
0 |
2.940 |
0 |
2.940 |
| MCP |
19.82289 |
0.0748150 |
1.979799 |
0.0488847 |
0 |
0 |
4.310 |
0 |
4.310 |
| SCAD |
19.80302 |
0.1020472 |
2.085949 |
0.0606429 |
0 |
0 |
6.824 |
0 |
6.824 |
Case 3: \(n < p\) - adaptive greedy
beta <- c(3,rep(0,5),1,rep(0,10),rep(0.05,3),rep(0,10),2,rep(0,120))
simu5_part2_ada <- run_simulation(nb_simu = 500, true_beta = beta,
n = 100, n_star = 1000, sigma = 3, cor_X = 0.25,
xlim = c(19.3,22), ylim = c(2,3.5),
xlab = expression(PE[y]),
ylab = expression(MSE[beta]),
title = "Simulation 5: n < p",
adaptive = TRUE, omitted_variables = 1)

kable(simu5_part2_ada)
| LS |
29.60585 |
0.2358299 |
12.311953 |
0.1829561 |
0 |
0 |
39.000 |
0 |
39.000 |
| AIC |
28.39794 |
0.1778518 |
11.129597 |
0.1605614 |
0 |
0 |
13.998 |
0 |
13.998 |
| BIC |
24.27648 |
0.2847263 |
6.810123 |
0.2441391 |
0 |
0 |
6.094 |
0 |
6.094 |
| HQ |
27.26201 |
0.1816258 |
10.122818 |
0.1832957 |
0 |
0 |
10.514 |
0 |
10.514 |
| lasso |
20.17443 |
0.1012597 |
2.725528 |
0.0690565 |
0 |
0 |
11.882 |
0 |
11.882 |
| PDC |
20.43240 |
0.0999867 |
2.992834 |
0.1206886 |
0 |
0 |
2.208 |
0 |
2.208 |
| enet |
20.41452 |
0.0936276 |
2.961706 |
0.0704891 |
0 |
0 |
17.166 |
0 |
17.166 |
| alasso |
19.87138 |
0.1050836 |
2.211785 |
0.0854961 |
0 |
0 |
2.844 |
0 |
2.844 |
| MCP |
19.99677 |
0.0954209 |
2.200610 |
0.0613539 |
0 |
0 |
4.478 |
0 |
4.478 |
| SCAD |
20.18132 |
0.0859469 |
2.539315 |
0.0528157 |
0 |
0 |
9.028 |
0 |
9.028 |
Case 4: \(n < p\) - nonadaptive greedy
beta <- c(3,rep(0,5),1,rep(0,10),rep(0.05,3),rep(0,10),2,rep(0,120))
simu5_part2_nonada <- run_simulation(nb_simu = 500, true_beta = beta,
n = 100, n_star = 1000, sigma = 3, cor_X = 0.25,
xlim = c(19.3,22), ylim = c(2,3.5),
xlab = expression(PE[y]),
ylab = expression(MSE[beta]),
title = "Simulation 5: n < p",
adaptive = FALSE, omitted_variables = 1)

kable(simu5_part2_nonada)
| LS |
29.60585 |
0.2358299 |
12.311953 |
0.1829561 |
0 |
0 |
39.000 |
0 |
39.000 |
| AIC |
27.33470 |
0.1732158 |
10.041626 |
0.1523226 |
0 |
0 |
13.372 |
0 |
13.372 |
| BIC |
23.35517 |
0.2004715 |
5.756583 |
0.2621362 |
0 |
0 |
5.708 |
0 |
5.708 |
| HQ |
25.95172 |
0.1607828 |
8.642288 |
0.1559651 |
0 |
0 |
9.788 |
0 |
9.788 |
| lasso |
20.17443 |
0.1012597 |
2.725528 |
0.0690565 |
0 |
0 |
11.882 |
0 |
11.882 |
| PDC |
20.28612 |
0.0818379 |
2.731973 |
0.1146394 |
0 |
0 |
2.362 |
0 |
2.362 |
| enet |
20.41452 |
0.0936276 |
2.961706 |
0.0704891 |
0 |
0 |
17.166 |
0 |
17.166 |
| alasso |
19.87138 |
0.1050836 |
2.211785 |
0.0854961 |
0 |
0 |
2.844 |
0 |
2.844 |
| MCP |
19.99677 |
0.0954209 |
2.200610 |
0.0613539 |
0 |
0 |
4.478 |
0 |
4.478 |
| SCAD |
20.18132 |
0.0859469 |
2.539315 |
0.0528157 |
0 |
0 |
9.028 |
0 |
9.028 |
Simulation 6
Case 1: \(n > p\) - adaptive greedy
beta <- c(3,rep(0,5),1,rep(0,10),rep(0.05,3),rep(0,10),2,rep(0,20))
simu6_part1_ada <- run_simulation(nb_simu = 500, true_beta = beta,
n = 100, n_star = 1000, sigma = 3, cor_X = 0.25,
xlab = expression(PE[y]),
ylab = expression(MSE[beta]),
title = "Simulation 6: n > p",
adaptive = TRUE)

kable(simu6_part1_ada)
| LS |
18.164562 |
0.1888375 |
10.4573591 |
0.1817820 |
0 |
100.0 |
6.000 |
45.000 |
51.000 |
| AIC |
12.128975 |
0.1194250 |
3.2084795 |
0.1279782 |
0 |
0.6 |
3.222 |
5.876 |
9.098 |
| BIC |
10.185307 |
0.0635619 |
1.1082839 |
0.0371106 |
0 |
0.0 |
2.804 |
1.084 |
3.888 |
| HQ |
10.865372 |
0.0800132 |
1.9031863 |
0.1085088 |
0 |
0.2 |
2.976 |
2.820 |
5.796 |
| lasso |
10.335688 |
0.0426948 |
1.3245968 |
0.0322219 |
0 |
1.6 |
3.446 |
7.608 |
11.054 |
| PDC |
9.967106 |
0.0555835 |
1.0096835 |
0.0413893 |
0 |
0.0 |
2.668 |
0.506 |
3.174 |
| enet |
10.550470 |
0.0426769 |
1.5172023 |
0.0412639 |
0 |
3.0 |
3.618 |
10.290 |
13.908 |
| alasso |
9.928824 |
0.0503249 |
0.9591637 |
0.0485525 |
0 |
0.2 |
2.798 |
1.298 |
4.096 |
| MCP |
10.071255 |
0.0448669 |
0.7723096 |
0.0387571 |
0 |
0.0 |
2.944 |
1.968 |
4.912 |
| SCAD |
10.073702 |
0.0494998 |
0.7556559 |
0.0294226 |
0 |
0.0 |
3.156 |
4.350 |
7.506 |
Case 2: \(n > p\) - nonadaptive greedy
beta <- c(3,rep(0,5),1,rep(0,10),rep(0.05,3),rep(0,10),2,rep(0,20))
simu6_part1_nonada <- run_simulation(nb_simu = 500, true_beta = beta,
n = 100, n_star = 1000, sigma = 3, cor_X = 0.25,
xlab = expression(PE[y]),
ylab = expression(MSE[beta]),
title = "Simulation 6: n > p",
adaptive = FALSE)

kable(simu6_part1_nonada)
| LS |
18.164562 |
0.1888375 |
10.4573591 |
0.1817820 |
0 |
100.0 |
6.000 |
45.000 |
51.000 |
| AIC |
11.983331 |
0.1228147 |
3.0357047 |
0.0768831 |
0 |
0.2 |
3.276 |
5.748 |
9.024 |
| BIC |
10.186848 |
0.0754578 |
1.1317777 |
0.0417861 |
0 |
0.0 |
2.882 |
1.180 |
4.062 |
| HQ |
10.968588 |
0.0926223 |
1.9411459 |
0.0960494 |
0 |
0.0 |
3.062 |
2.834 |
5.896 |
| lasso |
10.335688 |
0.0426948 |
1.3245968 |
0.0322219 |
0 |
1.6 |
3.446 |
7.608 |
11.054 |
| PDC |
9.856713 |
0.0555075 |
0.7599161 |
0.0909081 |
0 |
0.0 |
2.722 |
0.394 |
3.116 |
| enet |
10.550470 |
0.0426769 |
1.5172023 |
0.0412639 |
0 |
3.0 |
3.618 |
10.290 |
13.908 |
| alasso |
9.928824 |
0.0503249 |
0.9591637 |
0.0485525 |
0 |
0.2 |
2.798 |
1.298 |
4.096 |
| MCP |
10.071255 |
0.0448669 |
0.7723096 |
0.0387571 |
0 |
0.0 |
2.944 |
1.968 |
4.912 |
| SCAD |
10.073702 |
0.0494998 |
0.7556559 |
0.0294226 |
0 |
0.0 |
3.156 |
4.350 |
7.506 |
Case 3: \(n < p\) - adaptive greedy
beta <- c(3,rep(0,5),1,rep(0,10),rep(0.05,3),rep(0,10),2,rep(0,120))
simu6_part2_ada <- run_simulation(nb_simu = 500, true_beta = beta,
n = 100, n_star = 1000, sigma = 3, cor_X = 0.25,
xlab = expression(PE[y]),
ylab = expression(MSE[beta]),
title = "Simulation 6: n < p",
adaptive = TRUE)

kable(simu6_part2_ada)
| LS |
15.75937 |
0.0977847 |
6.924629 |
0.1181671 |
0 |
0.2 |
3.518 |
35.482 |
39.000 |
| AIC |
13.41529 |
0.1168050 |
4.560226 |
0.1222878 |
0 |
0.0 |
2.920 |
8.308 |
11.228 |
| BIC |
11.08738 |
0.1000759 |
2.087393 |
0.0904802 |
0 |
0.0 |
2.714 |
2.534 |
5.248 |
| HQ |
12.42498 |
0.1029060 |
3.394891 |
0.1293898 |
0 |
0.0 |
2.838 |
5.378 |
8.216 |
| lasso |
10.84788 |
0.0486911 |
1.797697 |
0.0535625 |
0 |
0.0 |
3.124 |
12.774 |
15.898 |
| PDC |
10.23524 |
0.0701200 |
1.187085 |
0.0278475 |
0 |
0.0 |
2.552 |
0.776 |
3.328 |
| enet |
11.05887 |
0.0551945 |
2.096985 |
0.0708282 |
0 |
0.0 |
3.222 |
16.416 |
19.638 |
| alasso |
10.05894 |
0.0606301 |
1.125238 |
0.0255999 |
0 |
0.0 |
2.576 |
1.500 |
4.076 |
| MCP |
10.20083 |
0.0464832 |
1.027896 |
0.0294854 |
0 |
0.0 |
2.754 |
3.040 |
5.794 |
| SCAD |
10.25321 |
0.0529682 |
1.030886 |
0.0228934 |
0 |
0.0 |
2.984 |
7.648 |
10.632 |
Case 4: \(n < p\) - nonadaptive greedy
beta <- c(3,rep(0,5),1,rep(0,10),rep(0.05,3),rep(0,10),2,rep(0,120))
simu6_part2_nonada <- run_simulation(nb_simu = 500, true_beta = beta,
n = 100, n_star = 1000, sigma = 3, cor_X = 0.25,
xlab = expression(PE[y]),
ylab = expression(MSE[beta]),
title = "Simulation 6: n < p",
adaptive = FALSE)

kable(simu6_part2_nonada)
| LS |
15.75937 |
0.0977847 |
6.924629 |
0.1181671 |
0 |
0.2 |
3.518 |
35.482 |
39.000 |
| AIC |
12.99853 |
0.1354686 |
3.972303 |
0.1060509 |
0 |
0.0 |
2.930 |
7.844 |
10.774 |
| BIC |
11.04486 |
0.0795333 |
2.013169 |
0.0826483 |
0 |
0.0 |
2.736 |
2.500 |
5.236 |
| HQ |
12.14950 |
0.1096684 |
3.169140 |
0.1036183 |
0 |
0.0 |
2.842 |
5.024 |
7.866 |
| lasso |
10.84788 |
0.0486911 |
1.797697 |
0.0535625 |
0 |
0.0 |
3.124 |
12.774 |
15.898 |
| PDC |
10.26517 |
0.0819376 |
1.225533 |
0.0295604 |
0 |
0.0 |
2.602 |
0.882 |
3.484 |
| enet |
11.05887 |
0.0551945 |
2.096985 |
0.0708282 |
0 |
0.0 |
3.222 |
16.416 |
19.638 |
| alasso |
10.05894 |
0.0606301 |
1.125238 |
0.0255999 |
0 |
0.0 |
2.576 |
1.500 |
4.076 |
| MCP |
10.20083 |
0.0464832 |
1.027896 |
0.0294854 |
0 |
0.0 |
2.754 |
3.040 |
5.794 |
| SCAD |
10.25321 |
0.0529682 |
1.030886 |
0.0228934 |
0 |
0.0 |
2.984 |
7.648 |
10.632 |